Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
This paper presents the study on the surface roughness model of workpiece in grinding. Based on the analysis of some previous studies, this research identifies the most outstanding model. After analyzing and evaluating its advantages, that model is considered in order to improve. The development of the model is implemented by putting into the roughness model two parameters that significantly affect the surface roughness in grinding, namely the elastic module of grinding wheel and workpiece material. The results of the application of the improved model to the prediction of surface roughness are compared with the roughness values when using CBN grinding wheel to grind C45 steel. It shows that the predictive roughness values are greatly close to the experiment results. The average discrepancy between predictive results with experiment results is approximately 8.11%. This study offers a promising ability to predict the surface roughness of a detail in grinding
The objective of this work is to investigate the effect of aqueous ammonia concentrations and pretreatment temperatures of rice hull to produce bioethanol. Aqueous Ammonia Soaking (AAS) and dilute acid were used to pretreat rice hull. The rice hull composition was analyzed by SEM and Chesson methods. AAS pretreatment was carried out at various aqueous ammonia concentrations of 5, 10, 15, 20, 25 % (v/v) and temperatures of 60, 70, 80 90, 100 oC. The result showed that the highest lignin reduction and glucan recovery were about 61.97%, 88.39%, respectively at ammonia concentration of 20% (v/v) and pretreated temperature of 100 oC. Furthermore, the result produced the highest glucose of about 241.8 mg g-1 and the bioethanol yield of 5.86%
In this study, the temperature profile of the sodium nitrate phase change material NaNO3 is characterized, using a spherical macro encapsulation technique to increase the heat transfer properties, simulating through computer tools the behavior of this material when it is used as an alternative source of energy for heat. exchange processes, where the primary energy source has interruptions in the heat supply, the data obtained show for the proposed model that the system is capable of maintaining the outlet temperature for at least 20s and a temperature drop of 50K for 60s, being promising data for the use of these materials in heat exchange processes as is the energy support of solar collectors
Internet of Things (IoT) is now one of the most challenging research fields that still has much to be discovered. Since it consists of a wide range of elements like devices, humans, animals, and others, there is a big need to find a simple way of its network simulation. Although there were previous trials to do this, a need exists to combine both modeling and simulation of IoT networks in one frame. In this work we propose a crossbreed approach that enables specialists to display IoT and reproduce OMNeT++, through giving mapping rules between the operator worldview and the OMNeT++ test system. The PDR and RTT results are plotted by varying the number of smart objects (SOs) and subnets for both large and low number scales. Increasing the number of subnetworks in a specific region badly influences both RTT and PDR
The government is actively encouraging food and energy independence to achieve development targets. So, it is necessary to make an inventory of existing rice fields. Identification of rice field area can be done using geographic information system (GIS). By doing so, a comparison of rice field a comparison of rice fields between data and interpretation results can be obtained and rice production in each district in the city of Lubuk Linggau can be predicted. Interpretation was carried out to get the classification of rice fields in the study area by using Landsat 8 Image. The interpretation of the image was carried out on a combination of band 653. The level of accuracy of the results of interpretation of rice fields in Lubuk Linggau City is 98.34%. The interpreted rice fields are smaller than the existing rice fields in the data, which is 55%
